Service providers and device manufacturers (e.g., wireless, cellular, etc.) are continually challenged to deliver value and convenience to consumers by, for example, providing compelling network services. One area of interest has been the development of location-based services to provide users of mobile devices (e.g., mobile phones, tablets, personal navigation devices, etc.) with navigation assistance to improve the quality of their travels (e.g., walking, driving, etc.). By way of example, many mobile devices are now equipped with global positioning system (GPS) receivers and mapping and/or navigation applications for presenting location-based information (e.g., maps, travel directions, route details, points of interest (POIs), etc.) to users. However, current location-based services are generally based on algorithms and methods that are driven by single coordinates as an input (e.g., a current location) or require the user to run the application for a number of minutes (e.g., 5-10 minutes) to record a location trace. These requirements limit the ability of the algorithms and methods of the location-based services to use map data—or past behavioral data of the user—to optimize results. Accordingly, service providers and device manufacturers face significant technical challenges in providing a location-based service that contemporaneously considers a user's recent movement history to create better predictions, more accurate results, more relevant renderings, or a combination thereof.